SAT-CTS delivers the first finite-time regret bounds for combinatorial semi-bandits with satisficing objectives, bounding satisficing regret by a constant when the threshold is realizable and yielding O((log T)^2) standard regret otherwise.
A behavioral model of rational choice,
2 Pith papers cite this work. Polarity classification is still indexing.
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Bounded-rational agents on networks reach higher stationary coordination probability when connectivity is uniform, with the probability increasing in rationality parameter beta and the partition function approximable by a Gaussian moment-generating function to show regular networks are optimal.
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Multi-User mmWave Beam and Rate Adaptation via Combinatorial Satisficing Bandits
SAT-CTS delivers the first finite-time regret bounds for combinatorial semi-bandits with satisficing objectives, bounding satisficing regret by a constant when the threshold is realizable and yielding O((log T)^2) standard regret otherwise.
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Learning to Coordinate over Networks with Bounded Rationality
Bounded-rational agents on networks reach higher stationary coordination probability when connectivity is uniform, with the probability increasing in rationality parameter beta and the partition function approximable by a Gaussian moment-generating function to show regular networks are optimal.